Lane detection with position embedding

Jun Xie; Jiacheng Han; Dezhen Qi; Feng Chen; Kaer Huang; Jianwei Shuai

doi:10.1117/12.2644351

12 October 2022 Lane detection with position embedding

Jun Xie, Jiacheng Han, Dezhen Qi, Feng Chen, Kaer Huang, Jianwei Shuai

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123420B (2022) https://doi.org/10.1117/12.2644351
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Recently, lane detection has made great progress in autonomous driving. RESA (REcurrent Feature-Shift Aggregator) is based on image segmentation. It presents a novel module to enrich lane feature after preliminary feature extraction with an ordinary CNN. For Tusimple dataset, there is not too complicated scene and lane has more prominent spatial features. On the basis of RESA, we introduce the method of position embedding to enhance the spatial features. The experimental results show that this method has achieved the best accuracy 96.93% on Tusimple dataset.

Citation Download Citation

Jun Xie, Jiacheng Han, Dezhen Qi, Feng Chen, Kaer Huang, and Jianwei Shuai "Lane detection with position embedding", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123420B (12 October 2022); https://doi.org/10.1117/12.2644351

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